Reporting and transparency in laboratory animal science: Past achievements, present concerns and future directions.

Abstract

Transparent reporting of animal research is both a scientific and ethical imperative and is linked to both research quality and the principles of Replacement, Reduction, and Refinement (3Rs). Persistent concerns about poor reproducibility, limited translation and research waste have driven reforms in reporting standards and data-sharing requirements. However, despite considerable progress over the past 60 years, substantial gaps remain. Many published studies still lack essential methodological detail, such as animal characteristics, welfare measures, bias minimization methods (such as randomization and blinding), and sample size justification. Non-reporting of negative or null results further distorts the evidence base. A major barrier to change has been inadequate training of researchers in best practices for experimental design and statistical analysis. We describe how standardized reporting frameworks can promote research quality and highlight tools available to assist the researcher in implementing best practices in study design, reporting, and data accessibility. Over the next decade, emerging applications such as automated compliance tools and AI-assisted screening will offer scalable approaches to adoption of reporting standards. Preclinical science itself will be profoundly altered by advances in alternative models, open data, and linked machine-readable research outputs that will shift the research culture from isolated studies to an integrated cumulative evidence ecosystem. However, an expanded evidence base will be of value only if methodological quality is prioritized over novelty. Embedding best practices at study inception coupled with transparency will enhance reproducibility, reduce waste, and strengthen the reliability and translational value of animal research.